Method and apparatus for utilizing channel state information in a wireless communication system

ABSTRACT

Techniques for transmitting data from a transmitter unit to a receiver unit in a multiple-input multiple-output (MIMO) communication system. In one method, at the receiver unit, a number of signals are received via a number of receive antennas, with the received signal from each receive antenna comprising a combination of one or more signals transmitted from the transmitter unit. The received signals are processed to derive channel state information (CSI) indicative of characteristics of a number of transmission channels used for data transmission. The CSI is transmitted back to the transmitter unit. At the transmitter unit, the CSI from the receiver unit is received and data for transmission to the receiver unit is processed based on the received CSI.

BACKGROUND

[0001] 1. Field

[0002] The present invention relates generally to data communication,and more specifically to a novel and improved method and apparatus forutilizing (full or partial) channel state information to provideimproved performance for a wireless communication system.

[0003] 2. Background

[0004] Wireless communication systems are widely deployed to providevarious types of communication such as voice, data, and so on. Thesesystems may be based on code division multiple access (CDMA), timedivision multiple access (TDMA), orthogonal frequency divisionmodulation (OFDM), or some other modulation techniques. OFDM systems canprovide high performance for some channel environments.

[0005] In a terrestrial communication system (e.g., a cellular system, abroadcast system, a multi-channel multi-point distribution system(MMDS), and others), an RF modulated signal from a transmitter unit mayreach a receiver unit via a number of transmission paths. Thecharacteristics of the transmission paths typically vary over time dueto a number of factors such as fading and multipath.

[0006] To provide diversity against deleterious path effects and improveperformance, multiple transmit and receive antennas may be used. If thetransmission paths between the transmit and receive antennas arelinearly independent (i.e., a transmission on one path is not formed asa linear combination of the transmissions on other paths), which isgenerally true to some extent, then the likelihood of correctlyreceiving a transmitted signal increases as the number of antennasincreases. Generally, diversity increases and performance improves asthe number of transmit and receive antennas increases.

[0007] A multiple-input multiple-output (MIMO) communication systememploys multiple (N_(T)) transmit antennas and multiple (N_(R)) receiveantennas for data transmission. A MIMO channel may be decomposed intoN_(C) independent channels, with N_(C)≦min {N_(T), N_(R)}. Each of theN_(C) independent channels is also referred to as a spatial subchannelof the MIMO channel and corresponds to a dimension. The MIMO system canprovide improved performance if the additional dimensionalities createdby the multiple transmit and receive antennas are utilized.

[0008] There is therefore a need in the art for techniques to utilizechannel state information (CSI) to take advantage of the additionaldimensionalities created by a MIMO system to provide improved systemperformance.

SUMMARY

[0009] Aspects of the invention provide techniques to process receivedsignals in a multiple-input multiple-output (MIMO) communication systemto recover transmitted signals, and to estimate the characteristics of aMIMO channel. Various receiver processing schemes may be used to derivechannel state information (CSI) indicative of the characteristics of thetransmission channels used for data transmission. The CSI is thenreported back to the transmitter system and used to adjust the signalprocessing (e.g., coding, modulation, and so on). In this manner, highperformance is achieved based on the determined channel conditions.

[0010] A specific embodiment of the invention provides a method fortransmitting data from a transmitter unit to a receiver unit in a MIMOcommunication system. In accordance with the method, at the receiverunit, a number of signals are received via a number of receive antennas,with the received signal from each receive antenna comprising acombination of one or more signals transmitted from the transmitterunit. The received signals are processed (e.g., via a channelcorrelation matrix inversion (CCMI) scheme, an unbiased minimum meansquare error (UMMSE) scheme, or some other receiver processing scheme)to derive CSI indicative of characteristics of a number of transmissionchannels used for data transmission. The CSI is encoded and transmittedback to the transmitter unit. At the transmitter unit, the CSI from thereceiver unit is received and data for transmission to the receiver unitis processed based on the received CSI.

[0011] The reported CSI may include full CSI or partial CSI. Full CSIincludes sufficient full-bandwidth characterization (e.g., the amplitudeand phase across the useable bandwidth) of the propagation path betweenall pairs of transmit and receive antennas. Partial CSI may include, forexample, the signal-to-noise-plus-interference (SNR) of the transmissionchannels. At the transmitter unit, the data for each transmissionchannel may be coded based on the SNR estimate for the transmissionchannel, and the coded data for each transmission channel may bemodulated in accordance with a modulation scheme selected based on theSNR estimate. For full-CSI processing, the modulation symbols are alsopre-processed prior to transmission in accordance with the received CSI.

[0012] The invention further provides methods, systems, and apparatusthat implement various aspects, embodiments, and features of theinvention, as described in further detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The features, nature, and advantages of the present inventionwill become more apparent from the detailed description set forth belowwhen taken in conjunction with the drawings in which like referencecharacters identify correspondingly throughout and wherein:

[0014]FIG. 1 is a diagram of a multiple-input multiple-output (MIMO)communication system capable of implementing various aspects andembodiments of the invention;

[0015]FIGS. 2A and 2B are block diagrams of an embodiment of a MIMOtransmitter system capable of performing partial-CSI processing andfull-CSI processing, respectively;

[0016]FIG. 3 is a block diagram of an embodiment of a MIMO transmittersystem which utilizes orthogonal frequency division modulation (OFDM);

[0017]FIG. 4 is a block diagram of a portion of a MIMO transmittersystem capable of providing different processing for differenttransmission types and which also employs OFDM;

[0018]FIGS. 5 and 6 are block diagrams of two embodiments of a receiversystem having multiple (N_(R)) receive antennas and capable ofprocessing a data transmission based on a channel correlation matrixinversion (CCMI) technique and an unbiased minimum mean square error(UMMSE), respectively;

[0019]FIG. 7A shows the average throughput for the MIMO system for threereceiver processing techniques and for different SNR values; and

[0020]FIG. 7B shows the cumulative probability distribution functions(CDF) for the three receiver processing techniques generated based onthe histogram of the data.

DETAILED DESCRIPTION

[0021]FIG. 1 is a diagram of a multiple-input multiple-output (MIMO)communication system 100 capable of implementing various aspects andembodiments of the invention. System 100 includes a first system 110 incommunication with a second system 150. System 100 can be operated toemploy a combination of antenna, frequency, and temporal diversity(described below) to increase spectral efficiency, improve performance,and enhance flexibility. In an aspect, system 150 can be operated todetermine the characteristics of the communication link and to reportchannel state information (CSI) back to system 110, and system 110 canbe operated to adjust the processing (e.g., encoding and modulation) ofdata to be transmitted based on the reported CSI.

[0022] Within system 110, a data source 112 provides data (i.e.,information bits) to a transmit (TX) data processor 114, which encodesthe data in accordance with a particular encoding scheme, interleaves(i.e., reorders) the encoded data based on a particular interleavingscheme, and maps the interleaved bits into modulation symbols for one ormore transmission channels used for transmitting the data. The encodingincreases the reliability of the data transmission. The interleavingprovides time diversity for the coded bits, permits the data to betransmitted based on an average signal-to-noise-plus-interference (SNR)for the transmission channels used for the data transmission, combatsfading, and further removes correlation between coded bits used to formeach modulation symbol. The interleaving may further provide frequencydiversity if the coded bits are transmitted over multiple frequencysubchannels. In accordance with an aspect of the invention, theencoding, interleaving, and symbol mapping (or a combination thereof)are performed based on the full or partial CSI available to system 110,as indicated in FIG. 1.

[0023] The encoding, interleaving, and symbol mapping at transmittersystem 110 can be performed based on numerous schemes. One specificscheme is described in U.S patent application Ser. No. 09/776,073,entitled “CODING SCHEME FOR A WIRELESS COMMUNICATION SYSTEM,” filed Feb.1, 2001, assigned to the assignee of the present application andincorporated herein by reference.

[0024] MIMO system 100 employs multiple antennas at both the transmitand receive ends of the communication link. These transmit and receiveantennas may be used to provide various forms of spatial diversity,including transmit diversity and receive diversity. Spatial diversity ischaracterized by the use of multiple transmit antennas and one or morereceive antennas. Transmit diversity is characterized by thetransmission of data over multiple transmit antennas. Typically,additional processing is performed on the data transmitted from thetransmit antennas to achieved the desired diversity. For example, thedata transmitted from different transmit antennas may be delayed orreordered in time, coded and interleaved across the available transmitantennas, and so on. Receive diversity is characterized by the receptionof the transmitted signals on multiple receive antennas, and diversityis achieved by simply receiving the signals via different signal paths.

[0025] System 100 may be operated in a number of different communicationmodes, with each communication mode employing antenna, frequency, ortemporal diversity, or a combination thereof. The communication modesmay include, for example, a “diversity” communication mode and a “MIMO”communication mode. The diversity communication mode employs diversityto improve the reliability of the communication link. In a commonapplication of the diversity communication mode, which is also referredto as a “pure” diversity communication mode, data is transmitted fromall available transmit antennas to a recipient receiver system. The purediversity communications mode may be used in instances where the datarate requirements are low or when the SNR is low, or when both are true.The MIMO communication mode employs antenna diversity at both ends ofthe communication link (i.e., multiple transmit antennas and multiplereceive antennas) and is generally used to both improve the reliabilityand increase the capacity of the communications link. The MIMOcommunication mode may further employ frequency and/or temporaldiversity in combination with the antenna diversity.

[0026] System 100 may further utilize orthogonal frequency divisionmodulation (OFDM), which effectively partitions the operating frequencyband into a number of (L) frequency subchannels (i.e., frequency bins).At each time slot (i.e., a particular time interval that may bedependent on the bandwidth of the frequency subchannel), a modulationsymbol may be transmitted on each of the L frequency subchannels.

[0027] System 100 may be operated to transmit data via a number oftransmission channels. As noted above, a MIMO channel may be decomposedinto N_(C) independent channels, with N_(C)≦min{N_(T), N_(R)}. Each ofthe N_(C) independent channels is also referred to as a spatialsubchannel of the MIMO channel. For a MIMO system not utilizing OFDM,there may be only one frequency subchannel and each spatial subchannelmay be referred to as a “transmission channel”. For a MIMO systemutilizing OFDM, each spatial subchannel of each frequency subchannel maybe referred to as a transmission channel. And for an OFDM system notoperated in the MIMO communication mode, there is only one spatialsubchannel and each frequency subchannel may be referred to as atransmission channel.

[0028] A MIMO system can provide improved performance if the additionaldimensionalities created by the multiple transmit and receive antennasare utilized. While this does not necessarily require knowledge of CSIat the transmitter, increased system efficiency and performance arepossible when the transmitter is equipped with CSI, which is descriptiveof the transmission characteristics from the transmit antennas to thereceive antennas. CSI may be categorized as either “full CSI” or“partial CSI”.

[0029] Full CSI includes sufficient characterization (e.g., theamplitude and phase) across the entire system bandwidth (i.e., eachfrequency subchannel) for the propagation path between eachtransmit-receive antenna pair in the N_(T)×N_(R) MIMO matrix. Full-CSIprocessing implies that (1) the channel characterization is available atboth the transmitter and receiver, (2) the transmitter computeseigenmodes for the MIMO channel (described below), determines modulationsymbols to be transmitted on the eigenmodes, linearly preconditions(filters) the modulation symbols, and transmits the preconditionedmodulation symbols, and (3) the receiver performs a complementaryprocessing (e.g., spatial matched filter) of the linear transmitprocessing based on the channel characterization to compute the N_(C)spatial matched filter coefficients needed for each transmission channel(i.e., each eigenmode). Full-CSI processing further entails processingthe data (e.g., selecting the proper coding and modulation schemes) foreach transmission channel based on the channel's eigenvalue (describedbelow) to derive the modulation symbols.

[0030] Partial CSI may include, for example, thesignal-to-noise-plus-interference (SNR) of the transmission channels(i.e., the SNR for each spatial subchannel for a MIMO system withoutOFDM, or the SNR for each frequency subchannel of each spatialsubchannel for a MIMO system with OFDM). Partial-CSI processing mayimply processing the data (e.g., selecting the proper coding andmodulation schemes) for each transmission channel based on the channel'sSNR.

[0031] Referring to FIG. 1, a TX MIMO processor 120 receives andprocesses the modulation symbols from TX data processor 114 to providesymbols suitable for transmission over the MIMO channel. The processingperformed by TX MIMO processor 120 is dependent on whether full orpartial CSI processing is employed, and is described in further detailbelow.

[0032] For full-CSI processing, TX MIMO processor 120 may demultiplexand precondition the modulation symbols. And for partial-CSI processing,TX MIMO processor 120 may simply demultiplex the modulation symbols. Thefull and partial-CSI MIMO processing is described in further detailbelow. For a MIMO system employing full-CSI processing but not OFDM, TXMIMO processor 120 provides a stream of preconditioned modulationsymbols for each transmit antenna, one preconditioned modulation symbolper time slot. Each preconditioned modulation symbol is a linear (andweighted) combination of N_(C) modulation symbols at a given time slotfor the N_(C) spatial subchannels, as described in further detail below.For a MIMO system employing full-CSI processing and OFDM, TX MIMOprocessor 120 provides a stream of preconditioned modulation symbolvectors for each transmit antenna, with each vector including Lpreconditioned modulation symbols for the L frequency subchannels for agiven time slot. For a MIMO system employing partial-CSI processing butnot OFDM, TX MIMO processor 120 provides a stream of modulation symbolsfor each transmit antenna, one modulation symbol per time slot. And fora MIMO system employing partial-CSI processing and OFDM, TX MIMOprocessor 120 provides a stream of modulation symbol vectors for eachtransmit antenna, with each vector including L modulation symbols forthe L frequency subchannels for a given time slot. For all casesdescribed above, each stream of (either unconditioned or preconditioned)modulation symbols or modulation symbol vectors is received andmodulated by a respective modulator (MOD) 122, and transmitted via anassociated antenna 124.

[0033] In the embodiment shown in FIG. 1, receiver system 150 includes anumber of receive antennas 152 that receive the transmitted signals andprovide the received signals to respective demodulators (DEMOD) 154.Each demodulator 154 performs processing complementary to that performedat modulator 122. The demodulated symbols from all demodulators 154 areprovided to a receive (RX) MIMO processor 156 and processed in a mannerdescribed below. The received modulation symbols for the transmissionchannels are then provided to a RX data processor 158, which performsprocessing complementary to that performed by TX data processor 114. Ina specific design, RX data processor 158 provides bit values indicativeof the received modulation symbols, deinterleaves the bit values, anddecodes the deinterleaved values to generate decoded bits, which arethen provided to a data sink 160. The received symbol de-mapping,deinterleaving, and decoding are complementary to the symbol mapping,interleaving, and encoding performed at transmitter system 110. Theprocessing by receiver system 150 is described in further detail below.

[0034] The spatial subchannels of a MIMO system (or more generally, thetransmission channels in a MIMO system with or without OFDM) typicallyexperience different link conditions (e.g., different fading andmultipath effects) and may achieve different SNR. Consequently, thecapacity of the transmission channels may be different from channel tochannel. This capacity may be quantified by the information bit rate(i.e., the number of information bits per modulation symbol) that may betransmitted on each transmission channel for a particular level ofperformance. Moreover, the link conditions typically vary with time. Asa result, the supported information bit rates for the transmissionchannels also vary with time. To more fully utilize the capacity of thetransmission channels, CSI descriptive of the link conditions may bedetermined (typically at the receiver unit) and provided to thetransmitter unit so that the processing can be adjusted (or adapted)accordingly. Aspects of the invention provide techniques to determineand utilize (full or partial) CSI to provide improved systemperformance.

MIMO Transmitter System with Partial-CSI Processing

[0035]FIG. 2A is a block diagram of an embodiment of a MIMO transmittersystem 110 a, which is one embodiment of the transmitter portion ofsystem 110 in FIG. 1. Transmitter system 110 a (which does not utilizeOFDM) is capable of adjusting its processing based on partial CSIreported by receiver system 150. System 110 a includes (1) a TX dataprocessor 114 a that receives and processes information bits to providemodulation symbols and (2) a TX MIMO processor 120 a that demultiplexesthe modulation symbols for the N_(T) transmit antennas.

[0036] TX data processor 114 a is one embodiment of TX data processor114 in FIG. 1, and many other designs may also be used for TX dataprocessor 114 and are within the scope of the invention. In the specificembodiment shown in FIG. 2A, TX data processor 114 a includes an encoder202, a channel interleaver 204, a puncturer 206, and a symbol mappingelement 208. Encoder 202 receives and encodes the information bits inaccordance with a particular encoding scheme to provide coded bits.Channel interleaver 204 interleaves the coded bits based on a particularinterleaving scheme to provide diversity. Puncturer 206 punctures zeroor more of the interleaved coded bits to provide the desired number ofcoded bits. And symbol mapping element 208 maps the unpunctured codedbit into modulation symbols for one or more transmission channels usedfor transmitting the data.

[0037] Although not shown in FIG. 2A for simplicity, pilot data (e.g.,data of known pattern) may be encoded and multiplexed with the processedinformation bits. The processed pilot data may be transmitted (e.g., ina time division multiplexed manner) in all or a subset of thetransmission channels used to transmit the information bits. The pilotdata may be used at the receiver to perform channel estimation, as isknown in the art and described in further detail below.

[0038] As shown in FIG. 2A, the encoding and modulation may be adjustedbased on the partial-CSI reported by receiver system 150. In anembodiment, adaptive encoding is achieved by using a fixed base code(e.g., a rate ⅓ Turbo code) and adjusting the puncturing to achieve thedesired code rate, as supported by the SNR of the transmission channelused to transmit data. Alternatively, different coding schemes may beused based on the reported partial-CSI (as indicated by the dashed arrowinto block 202). For example, each of the transmission channels may becoded with an independent code. With this coding scheme, a successive“nulling/equalization and interference cancellation” receiver processingscheme may be used to detect and decode the data streams to derive amore reliable estimate of the transmitted data streams. One suchreceiver processing scheme is described by P. W. Wolniansky, et al in apaper entitled “V-BLAST: An Architecture for Achieving Very High DataRates over the Rich-Scattering Wireless Channel”, Proc. ISSSE-98, Pisa,Italy, and incorporated herein by reference.

[0039] For each transmission channel, symbol mapping element 208 can bedesigned to group sets of unpunctured coded bits to form non-binarysymbols, and to map the non-binary symbols into points in a signalconstellation corresponding to a particular modulation scheme (e.g.,QPSK, M-PSK, M-QAM, or some other scheme) selected for that transmissionchannel. Each mapped point corresponds to a modulation symbol. Thenumber of information bits that may be transmitted for each modulationsymbol for a particular level of performance (e.g., one percent packeterror rate) is dependent on the SNR of the transmission channel. Thus,the coding scheme and modulation scheme for each transmission channelmay be selected based on the reported partial-CSI. The channelinterleaving may also be adjusted based on the reported partial-CSI (asindicated by the dashed arrow into block 204).

[0040] Table 1 lists various combinations of coding rate and modulationscheme that may be used for a number of SNR ranges. The supported bitrate for each transmission channel may be achieved using any one of anumber of possible combinations of coding rate and modulation scheme.For example, one information bit per symbol may be achieved using (1) acoding rate of ½ and QPSK modulation, (2) a coding rate of ⅓ and 8-PSKmodulation, (3) a coding rate of ¼ and 16-QAM, or some other combinationof coding rate and modulation scheme. In Table 1, QPSK, 16-QAM, and64-QAM are used for the listed SNR ranges. Other modulation schemes suchas 8-PSK, 32-QAM, 128-QAM, and so on, may also be used and are withinthe scope of the invention. TABLE 1 SNR # of Information Modulation # ofCoded Coding Range Bits/Symbol Symbol Bits/Symbol Rate 1.5-4.4 1 QPSK 21/2 4.4-6.4 1.5 QPSK 2 3/4  6.4-8.35 2 16-QAM 4 1/2 8.35-10.4 2.5 16-QAM4 5/8 10.4-12.3 3 16-QAM 4 3/4  12.3-14.15 3.5 64-QAM 6  7/1214.15-15.55 4 64-QAM 6 2/3 15.55-17.35 4.5 64-QAM 6 3/4 >17.35 5 64-QAM6 5/6

[0041] The modulation symbols from TX data processor 114 a are providedto a TX MIMO processor 120 a, which is one embodiment of TX MIMOprocessor 120 in FIG. 1. Within TX MIMO processor 120 a, a demultiplexer214 demultiplexes the received modulation symbols into a number of(N_(T)) streams of modulation symbols, one stream for each antenna usedto transmit the modulation symbols. Each stream of modulation symbols isprovided to a respective modulator 122. Each modulator 122 converts themodulation symbols into an analog signal, and further amplifies,filters, quadrature modulates, and upconverts the signal to generate amodulated signal suitable for transmission over the wireless link.

[0042] If the number of spatial subchannels is less than the number ofavailable transmit antennas (i.e., N_(C)<N_(T)) then various schemes maybe used for the data transmission. In one scheme, N_(C) modulationsymbol steams are generated and transmitted on a subset (i.e., N_(C)) ofthe available transmitted antennas. The remaining (N_(T)−N_(C)) transmitantennas are not used for the data transmission. In another scheme, theadditional degrees of freedom provided by the (N_(T)−N_(C)) additionaltransmit antennas are used to improve the reliability of the datatransmission. For this scheme, each of one or more data streams may beencoded, possibly interleaved, and transmitted over multiple transmitantennas. The use of multiple transmit antennas for a data streamincreases diversity and improves reliability against deleterious patheffects.

MIMO Transmitter System with Full-CSI Processing

[0043]FIG. 2B is a block diagram of an embodiment of a MIMO transmittersystem 110 b (which does not utilize OFDM) capable of processing databased on full CSI reported by receiver system 150. The information bitsare encoded, interleaved, and symbol mapped by a TX data processor 114to generate modulation symbols. The coding and modulation may beadjusted based on the available full-CSI reported by the receiversystem, and may be performed as described above for MIMO transmittersystem 110 a.

[0044] Within a TX MIMO processor 120 b, a channel MIMO processor 212demultiplexes the received modulation symbols into a number of (N_(C))modulation symbol streams, one stream for each spatial subchannel (i.e.,eigenmode) used to transmit the modulation symbols. For full-CSIprocessing, channel MIMO processor 212 preconditions the N_(C)modulation symbols at each time slot to generate N_(T) preconditionedmodulation symbols, as follows: $\begin{matrix}{\begin{bmatrix}x_{1} \\x_{2} \\\vdots \\x_{N_{T}}\end{bmatrix} = {\left\lbrack \quad \begin{matrix}{e_{11},} & {e_{12},} & \quad & e_{1N_{c}} \\{e_{21},} & {e_{22},} & \quad & e_{2N_{c}} \\\quad & \quad & \quad & \quad \\{e_{N_{T}1},} & {e_{N_{T}1},} & \quad & e_{N_{T}N_{c}}\end{matrix}\quad \right\rbrack \cdot \begin{bmatrix}b_{1} \\b_{2} \\\vdots \\b_{N_{c}}\end{bmatrix}}} & {{Eq}\quad (1)}\end{matrix}$

[0045] where

[0046] b₁, b₂, . . . and b_(Nc) are respectively the modulation symbolsfor the spatial subchannels 1, 2, . . . N_(Nc), where each of the N_(C)modulation symbols may be generated using, for example, M-PSK, M-QAM, orsome other modulation scheme;

[0047] e_(ij) are elements of an eigenvector matrix E related to thetransmission characteristics from the transmit antennas to the receiveantennas; and

[0048] x₁, x₂, . . . x_(N) _(T) are the preconditioned modulationsymbols, which can be expressed as:

x ₁ =b ₁ ·e ₁₁ +b ₂ ·e ₁₂ + . . . +b _(N) _(C) ·e _(1N) _(C) ,

x ₂ =b ₁ ·e ₂₁ +b ₂ ·e ₂₂ + . . . +b _(N) _(C) ·e _(2N) _(C),

[0049] and

x _(N) _(T) =b ₁ ·e _(N) _(T) ₁ +b ₂ ·e _(N) _(T) ₂ + . . . +b _(N) _(C)·e _(N) _(T) _(N) _(C) .

[0050]  The eigenvector matrix E may be computed by the transmitter oris provided to the transmitter by the receiver.

[0051] For full-CSI processing, each preconditioned modulation symbol,x_(i), for a particular transmit antenna represents a linear combinationof (weighted) modulation symbols for up to N_(C) spatial subchannels.The modulation scheme employed for each of the modulation symbol x_(i)is based on the effective SNR of that eigenmode and is proportional toan eigenvalue, λ_(i) (described below). Each of the N_(C) modulationsymbols used to generate each preconditioned modulation symbol may beassociated with a different signal constellation. For each time slot,the N_(T) preconditioned modulation symbols generated by channel MIMOprocessor 212 are demultiplexed by a demultiplexer 214 and provided toN_(T) modulators 122.

[0052] The full-CSI processing may be performed based on the availableCSI and on the selected transmit antennas. The full-CSI processing mayalso be enabled and disabled selectively and dynamically. For example,the full-CSI processing may be enabled for a particular datatransmission and disabled for some other data transmissions. Thefull-CSI processing may be enabled under certain conditions, forexample, when the communication link has adequate SNR.

MIMO Transmitter System with OFDM

[0053]FIG. 3 is a block diagram of an embodiment of a MIMO transmittersystem 110 c, which utilizes OFDM and is capable of adjusting itsprocessing based on full or partial CSI. The information bits areencoded, interleaved, punctured, and symbol mapped by a TX dataprocessor 114 to generate modulation symbols. The coding and modulationmay be adjusted based on the available full or partial CSI reported bythe receiver system. For a MIMO system with OFDM, the modulation symbolsmay be transmitted on multiple frequency subchannels and from multipletransmit antennas. When operating in a pure MIMO communication mode, thetransmission on each frequency subchannel and from each transmit antennarepresents non-duplicated data.

[0054] Within a MIMO processor 120 c, a demultiplexer (DEMUX) 310receives and demultiplexes the modulation symbols into a number ofsubchannel symbol streams, S₁ through S_(L), one subchannel symbolstream for each frequency subchannel used to transmit the symbols.

[0055] For full-CSI processing, each subchannel symbol stream is thenprovided to a respective subchannel MIMO processor 312. Each subchannelMIMO processor 312 demultiplexes the received subchannel symbol streaminto a number of (up to N_(C)) symbol substreams, one symbol substreamfor each spatial subchannel used to transmit the modulation symbols. Forfull-CSI processing in an OFDM system, the eigenmodes are derived andapplied on a per frequency subchannel basis. Thus, each subchannel MIMOprocessors 312 preconditions up to N_(C) modulation symbols inaccordance with equation (1) to generate preconditioned modulationsymbols. Each preconditioned modulation symbol for a particular transmitantenna of a particular frequency subchannel represents a linearcombination of (weighted) modulation symbols for up to N_(C) spatialsubchannels.

[0056] For full-CSI processing, the (up to) N_(T) preconditionedmodulation symbols generated by each subchannel MIMO processor 312 foreach time slot are demultiplexed by a respective demultiplexer 314 andprovided to (up to) N_(T) symbol combiners 316 a through 316 t. Forexample, subchannel MIMO processor 312 a assigned to frequencysubchannel 1 may provide up to N_(T) preconditioned modulation symbolsfor frequency subchannel 1 of antennas 1 through N_(T). Similarly,subchannel MIMO processor 3121 assigned to frequency subchannel L mayprovide up to N_(T) symbols for frequency subchannel L of antennas 1through N_(T).

[0057] And for partial-CSI processing, each subchannel symbol stream, S,is demultiplexed by a respective demultiplexer 314 and provided to (upto) N_(T) symbol combiners 316 a through 316 t. The processing bysubchannel MIMO processor 312 is bypassed for partial-CSI processing.

[0058] Each combiner 316 receives the modulation symbols for up to Lfrequency subchannels, combines the symbols for each time slot into amodulation symbol vector V, and provides the modulation symbol vector tothe next processing stage (i.e., modulator 122).

[0059] MIMO processor 120 c thus receives and processes the modulationsymbols to provide N_(T) modulation symbol vectors, V₁ through V_(T),one modulation symbol vector for each transmit antenna. Each modulationsymbol vector V covers a single time slot, and each element of themodulation symbol vector V is associated with a specific frequencysubchannel having a unique subcarrier on which the modulation symbol isconveyed. If not operating in a “pure” MIMO communication mode, some ofthe modulation symbol vectors may have duplicate or redundantinformation on specific frequency subchannels for different transmitantennas.

[0060]FIG. 3 also shows an embodiment of modulator 122 for OFDM. Themodulation symbol vectors V₁ through V_(T) from MIMO processor 120 c areprovided to modulators 122 a through 122 t, respectively. In theembodiment shown in FIG. 3, each modulator 122 includes an inverse FastFourier Transform (IFFT) 320, cycle prefix generator 322, and anupconverter 324.

[0061] IFFT 320 converts each received modulation symbol vector into itstime-domain representation (which is referred to as an OFDM symbol)using IFFT. IFFT 320 can be designed to perform the IFFT on any numberof frequency subchannels (e.g., 8, 16, 32, and so on). In an embodiment,for each modulation symbol vector converted to an OFDM symbol, cycleprefix generator 322 repeats a portion of the time-domain representationof the OFDM symbol to form a transmission symbol for a specific transmitantenna. The cyclic prefix insures that the transmission symbol retainsits orthogonal properties in the presence of multipath delay spread,thereby improving performance against deleterious path effects. Theimplementation of IFFT 320 and cycle prefix generator 322 is known inthe art and not described in detail herein.

[0062] The time-domain representations from each cycle prefix generator322 (i.e., the transmission symbols for each antenna) are then processed(e.g., converted into an analog signal, modulated, amplified, andfiltered) by upconverter 324 to generate a modulated signal, which isthen transmitted from the respective antenna 124.

[0063] OFDM modulation is described in further detail in a paperentitled “Multicarrier Modulation for Data Transmission: An Idea WhoseTime Has Come,” by John A. C. Bingham, IEEE Communications Magazine, May1990, which is incorporated herein by reference.

[0064] A number of different types of transmission (e.g., voice,signaling, data, pilot, and so on) may be transmitted by a communicationsystem. Each of these transmissions may require different processing.

[0065]FIG. 4 is a block diagram of a portion of a MIMO transmittersystem 110 d capable of providing different processing for differenttransmission types and which also employs OFDM. The aggregate inputdata, which includes all information bits to be transmitted by system110 d, is provided to a demultiplexer 408. Demultiplexer 408demultiplexes the input data into a number of (K) channel data streams,B₁ through B_(K). Each channel data stream may correspond to, forexample, a signaling channel, a broadcast channel, a voice call, or apacket data transmission. Each channel data stream is provided to arespective TX data processor 114 that encodes the data using aparticular encoding scheme selected for that channel data stream,interleaves the encoded data based on a particular interleaving scheme,and maps the interleaved bits into modulation symbols for one or moretransmission channels used for transmitting that channel data stream.

[0066] The encoding can be performed on a per transmission basis (i.e.,on each channel data stream, as shown in FIG. 4). However, the encodingmay also be performed on the aggregate input data (as shown in FIG. 1),on a number of channel data streams, on a portion of a channel datastream, across a set of frequency subchannels, across a set of spatialsubchannels, across a set of frequency subchannels and spatialsubchannels, across each frequency subchannel, on each modulationsymbol, or on some other unit of time, space, and frequency.

[0067] The modulation symbol stream from each TX data processor 114 maybe transmitted on one or more frequency subchannels and via one or morespatial subchannels of each frequency subchannel. A TX MIMO processor120 d receives the modulation symbol streams from TX data processors114. Depending on the communication mode to be used for each modulationsymbol stream, TX MIMO processor 120 d may demultiplex the modulationsymbol stream into a number of subchannel symbol streams. In theembodiment shown in FIG. 4, modulation symbol stream S₁ is transmittedon one frequency subchannel and modulation symbol stream SK istransmitted on L frequency subchannels. The modulation stream for eachfrequency subchannel is processed by a respective subchannel MIMOprocessor 412, demultiplexed by demultiplexer 414, and combined bycombiner 416 (e.g., in similar manner as that described in FIG. 3) toform a modulation symbol vector for each transmit antenna.

[0068] In general, a transmitter system codes and modulates data foreach transmission channel based on information descriptive of thatchannel's transmission capability. This information is typically in theform of full CSI or partial CSI described above. The full/partial-CSIfor the transmission channels used for data transmission is typicallydetermined at the receiver system and reported back to the transmittersystem, which then uses the information to adjust the coding andmodulation accordingly. The techniques described herein are applicablefor multiple parallel transmission channels supported by MIMO, OFDM, orany other communication scheme (e.g., a CDMA scheme) capable ofsupporting multiple parallel transmission channels.

[0069] MIMO processing is described in further detail in U.S patentapplication Ser. No. 09/532,492, entitled “HIGH EFFICIENCY, HIGHPERFORMANCE COMMUNICATIONS SYSTEM EMPLOYING MULTI-CARRIER MODULATION,”filed Mar. 22, 2000, assigned to the assignee of the present applicationand incorporated herein by reference.

MIMO Receiver System

[0070] Aspects of the invention provide techniques to process thereceived signals in a MIMO system to recover the transmitted data, andto estimate the characteristics of the MIMO channel. The estimatedchannel characteristics may then be reported back to the transmittersystem and used to adjust the signal processing (e.g., coding,modulation, and so on). In this manner, high performance is achievedbased on the determined channel conditions. The receiver processingtechniques described herein include a channel correlation matrixinversion (CCMI) technique, an unbiased minimum mean square error(UMMSE) technique, and a full-CSI technique, all of which are describedin further detail below. Other receiver processing techniques may alsobe used and are within the scope of the invention.

[0071]FIG. 1 shows receiver system 150 having multiple (N_(R)) receiveantennas and capable of processing a data transmission. The transmittedsignals from up to N_(T) transmit antennas are received by each of N_(R)antennas 152 a through 152 r and routed to a respective demodulator(DEMOD) 154 (which is also referred to as a front-end processor). Forexample, receive antenna 152 a may receive a number of transmittedsignals from a number of transmit antennas, and receive antenna 152 rmay similarly receive multiple transmitted signals. Each demodulator 154conditions (e.g., filters and amplifies) the received signal,downconverts the conditioned signal to an intermediate frequency orbaseband, and digitizes the downconverted signal. Each demodulator 154may further demodulate the digitized samples with a received pilot togenerate received modulation symbols, which are provided to RX MIMOprocessor 156.

[0072] If OFDM is employed for the data transmission, each demodulator154 further performs processing complementary to that performed bymodulator 122 shown in FIG. 3. In this case, each demodulator 154includes an FFT processor (not shown) that generates transformedrepresentations of the samples and provides a stream of modulationsymbol vectors, with each vector including L modulation symbols for Lfrequency subchannels. The modulation symbol vector streams from the FFTprocessors of all demodulators are then provided to ademultiplexer/combiner (not shown in FIG. 5), which first “channelizes”the modulation symbol vector stream from each FFT processor into anumber of (up to L) subchannel symbol streams. Each of (up to) Lsubchannel symbol streams may then be provided to a respective RX MIMOprocessor 156.

[0073] For a MIMO system not utilizing OFDM, one RX MIMO processor 156may be used to perform the MIMO processing for the modulation symbolsfrom the N_(R) received antennas. And for a MIMO system utilizing OFDM,one RX MIMO processor 156 may be used to perform the MIMO processing forthe modulation symbols from the N_(R) received antennas for each of theL frequency subchannels used for data transmission.

[0074] In a MIMO system with N_(T) transmit antennas and N_(R) receiveantennas, the received signals at the output of the N_(R) receiveantennas may be expressed as:

r=Hx+n,  Eq(2)

[0075] where r is the received symbol vector (i.e., the N_(R)×1 vectoroutput from the MIMO channel, as measured at the receive antennas), H isthe N_(R)×N_(T) channel coefficient matrix that gives the channelresponse for the N_(T) transmit antennas and N_(R) receive antennas at aspecific time, x is the transmitted symbol vector (i.e., the N_(T)×1vector input into the MIMO channel), and n is an N_(R)×1 vectorrepresenting noise plus interference. The received symbol vector rincludes N_(R) modulation symbols from N_(R) signals received via N_(R)receive antennas at a specific time. Similarly, the transmitted symbolvector x includes N_(T) modulation symbols in N_(T) signals transmittedvia N_(T) transmit antennas at a specific time.

MIMO Receiver Utilizing CCMI Technique

[0076] For the CCMI technique, the receiver system first performs achannel matched filter operation on the received symbol vector r, andthe filtered output can be expressed as:

H ^(H) r=H ^(H) Hx+H ^(H) n,  Eq(3)

[0077] where the superscript “^(H)” represents transpose and complexconjugate. A square matrix R may be used to denote the product of thechannel coefficient matrix H with its conjugate-transpose H^(H) (i.e.,R=H^(H)H).

[0078] The channel coefficient matrix H may be derived, for example,from pilot symbols transmitted along with the data. In order to performoptimal reception and to estimate the SNR of the transmission channels,it is often convenient to insert some known symbols into the transmitdata stream and to transmit the known symbols over one or moretransmission channels. Such known symbols are also referred to as pilotsymbols or pilot signals. Methods for estimating a single transmissionchannel based on a pilot signal or the data transmission may be found ina number of papers available in the art. One such channel estimationmethod is described by F. Ling in a paper entitled “Optimal Reception,Performance Bound, and Cutoff-Rate Analysis of References-AssistedCoherent CDMA Communications with Applications,” IEEE Transaction OnCommunication, October 1999. This or some other channel estimationmethod may be extended to matrix form to derive the channel coefficientmatrix H.

[0079] An estimate of the transmitted symbol vector, x′, may be obtainedby multiplying the signal vector H^(H)r with the inverse (orpseudo-inverse) of R, which can be expressed as: $\begin{matrix}\begin{matrix}{{\underset{\_}{x}}^{\prime} = \quad {R^{- 1}H^{H}\underset{\_}{r}}} \\{= \quad {\underset{\_}{x} + {R^{- 1}H^{H}\underset{\_}{n}}}} \\{= \quad {\underset{\_}{x} + {{\underset{\_}{n}}^{\prime}.`}}}\end{matrix} & {{Eq}\quad (4)}\end{matrix}$

[0080] From the above equations, it can be observed that the transmittedsymbol vector x may be recovered by matched filtering (i.e., multiplyingwith the matrix H^(H)) the received symbol vector r and then multiplyingthe filtered result with the inverse square matrix R⁻¹.

[0081] The SNR of the transmission channels may be determined asfollows. The autocorrelation matrix φ_(nn) of the noise vector n isfirst computed from the received signal. In general, φ_(nn) is aHermitian matrix, i.e., it is complex-conjugate-symmetric. If thecomponents of the channel noise are uncorrelated and further independentand identically distributed (iid), the autocorrelation matrix φ_(nn) ofthe noise vector n can be expressed as: $\begin{matrix}\begin{matrix}{{\varphi_{nn} = \quad {\sigma_{n}^{2}I}},{and}} \\{{\varphi_{nn}^{- 1} = \quad {\frac{1}{\sigma_{n}^{2}}I}},}\end{matrix} & {{Eq}\quad (5)}\end{matrix}$

[0082] where I is the identity matrix (i.e., ones along the diagonal andzeros otherwise) and σ_(n) ² is the noise variance of the receivedsignals. The autocorrelation matrix φ_(n′n′) of the post-processed noisevector n′ (i.e., after the matched filtering and pre-multiplication withthe matrix R⁻¹) can be expressed as: $\begin{matrix}{\begin{matrix}{\varphi_{n^{\prime}n^{\prime}} = {E\left\lbrack {{\underset{\_}{n}}^{\prime}{\underset{\_}{n}}^{\prime \quad H}} \right\rbrack}} \\{= {\sigma_{n}^{2}R^{- 1}}}\end{matrix}\quad} & {{Eq}\quad (6)}\end{matrix}$

[0083] From equation (6), the noise variance σ_(n′) ² of the i-thelement of the post-processed noise n′ is equal to σ_(n) ²{haeck over(r)}_(ll), where {haeck over (r)}_(il) is the i-th diagonal element ofR⁻¹. For a MIMO system not utilizing OFDM, the i-th element isrepresentative of the i-th receive antenna. And if OFDM is utilized,then the subscript “i” may be decomposed into a subscript “jk”, where“j” represents the j-th frequency subchannel and “k” represents the k-thspatial subchannel corresponding to the k-th receive antenna.

[0084] For the CCMI technique, the SNR of the i-th element of thereceived symbol vector after processing (i.e., the i-th element of x′)can be expressed as: $\begin{matrix}{{SNR}_{i} = {\frac{{\overset{\_}{x_{i}^{\prime}}}^{2}}{\sigma_{n^{\prime}}^{2}}.}} & {{Eq}\quad (7)}\end{matrix}$

[0085] If the variance of the i-th transmitted symbol {overscore(|x′_(i)|²)} is equal to one (1.0) on the average, the SNR of thereceive symbol vector may be expressed as:${SNR}_{i} = {\frac{1}{{\overset{\Cup}{r}}_{ii}\sigma_{n}^{2}}.}$

[0086] The noise variance may be normalized by scaling the i-th elementof the received symbol vector by 1/{square root}{square root over(r)}_(ii).

[0087] The scaled signals from the N_(R) receive antennas may be summedtogether to form a combined signal, which may be expressed as:$\begin{matrix}{x_{total}^{\prime} = {\sum\limits_{i = 1}^{N_{R}}{\frac{x_{i}^{\prime}}{{\overset{\Cup}{r}}_{ii}}.}}} & {{Eq}\quad (8)}\end{matrix}$

[0088] The SNR of the combined signal, SN_(total), would then have amaximal combined SNR that is equal to the sum of the SNR of the signalsfrom the N_(R) receive antennas. The combined SNR may be expressed as:$\begin{matrix}{{SNR}_{total} = {{\sum\limits_{i = 1}^{N_{R}}{SNR}_{i}} = {\frac{1}{\sigma_{n}^{2}}{\sum\limits_{i = 1}^{N_{R}}{\frac{1}{{\overset{\Cup}{r}}_{ii}}.}}}}} & {{Eq}\quad (9)}\end{matrix}$

[0089]FIG. 5 shows an embodiment of an RX MIMO processor 156 a, which iscapable of implementing the CCMI processing described above. Within RXMIMO processor 156 a, the modulation symbols from the N_(R) receiveantennas are multiplexed by a multiplexer 512 to form a stream ofreceived modulation symbol vectors r. The channel coefficient matrix Hmay be estimated based on pilot signals similar to conventional pilotassisted single and multi-carrier systems, as is known in the art. Thematrix R is then computed according to R=H^(H)H as shown above. Thereceived modulation symbol vectors r are then filtered by a match filter514, which pre-multiplies each vector r with the conjugate-transposechannel coefficient matrix H^(H), as shown above in equation (3). Thefiltered vectors are further pre-multiplied by a multiplier 516 with theinverse square matrix R⁻¹ to form an estimate x′ of the transmittedmodulation symbol vector x, as shown above in equation (4).

[0090] For certain communication modes, the subchannel symbol streamsfrom all antennas used for the transmission of the channel data streammay be provided to a combiner 518, which combines redundant informationacross time, space, and frequency. The combined modulation symbols x″are then provided to RX data processor 158. For some other communicationmodes, the estimated modulation symbols x′ may be provided directly toRX data processor 158 (not shown in FIG. 5).

[0091] RX MIMO processor 156 a thus generates a number of independentsymbol streams corresponding to the number of transmission channels usedat the transmitter system. Each symbol stream includes post-processedmodulation symbols, which correspond to the modulation symbols prior tothe full/partial-CSI processing at the transmitter system. The(post-processed) symbol streams are then provided to RX data processor158.

[0092] Within RX data processor 158, each post-processed symbol streamof modulation symbols is provided to a respective demodulation elementthat implements a demodulation scheme (e.g., M-PSK, M-QAM) that iscomplementary to the modulation scheme used at the transmitter systemfor the transmission channel being processed. For the MIMO communicationmode, the demodulated data from all assigned demodulators may then bedecoded independently or multiplexed into one channel data stream andthen decoded, depending upon the coding and modulation method employedat the transmitter unit. Each channel data stream may then be providedto a respective decoder that implements a decoding scheme complementaryto that used at the transmitter unit for the channel data stream. Thedecoded data from each decoder represents an estimate of the transmitteddata for that channel data stream.

[0093] The estimated modulation symbols x′ and/or the combinedmodulation symbols x″ are also provided to a CSI processor 520, whichdetermines full or partial CSI for the transmission channels andprovides the full/partial-CSI to be reported back to transmitter system110. For example, CSI processor 520 may estimate the noise covariancematrix Φ_(nn) of the i-th transmission channel based on the receivedpilot signal and then compute the SNR based on equations (7) and (9).The SNR can be estimated similar to conventional pilot assisted singleand multi-carrier systems, as is known in the art. The SNR for thetransmission channels comprises the partial-CSI that is reported back tothe transmitter system. The modulation symbols are further provided to achannel estimator 522 and a matrix processor 524 that respectivelyestimates the channel coefficient matrix H and derive the square matrixR. A controller 530 couples to RX MIMO processor 156 a and RX dataprocessor 158 and directs the operation of these units.

MIMO Receiver Utilizing UMMSE Technique

[0094] For the UMMSE technique, the receiver system performs amultiplication of the received symbol vector r with a matrix M to derivean initial MMSE estimate {circumflex over (x)} of the transmitted symbolvector x, which can be expressed as:

î=Mr.  Eq(10)

[0095] The matrix M is selected such that the mean square error of theerror vector e between the initial MMSE estimate {circumflex over (x)}and the transmitted symbol vector x (i.e., e={circumflex over (x)}−x) isminimized.

[0096] To determine M, a cost function ε can first be expressed as:$\begin{matrix}{ɛ = \quad {E\left\{ {{\underset{\_}{e}}^{H}\underset{\_}{e}} \right\}}} \\{= \quad {E\left\{ {\left\lbrack {{{\underset{\_}{r}}^{H}M^{H}} - {\underset{\_}{x}}^{H}} \right\rbrack \left\lbrack {{M\underset{\_}{r}} - \underset{\_}{x}} \right\rbrack} \right\}}} \\{= \quad {E{\left\{ {{{\underset{\_}{r}}^{H}M^{H}M\underset{\_}{r}} - {2\quad R\quad {e\left\lbrack {{\underset{\_}{x}}^{H}M\underset{\_}{r}} \right\rbrack}} + {{\underset{\_}{x}}^{H}x}} \right\}.}}}\end{matrix}$

[0097] To minimize the cost function ε, a derivative of the costfunction can be taken with respect to M, and the result can be set tozero, as follows:${\frac{\partial\quad}{\partial M}ɛ} = {{{2\left( {{H\quad H^{H}} + \varphi_{n\quad n}} \right)M^{H}} - {2H}} = 0.}$

[0098] Using the equalities E{xx^(H)}=I, E{rr^(H)}=HH^(H)+φ_(nn), andE{rx^(H)}=H, the following is obtained:

2(HH ^(H)+φ_(nn))M ^(H)=2H.

[0099] Thus, the matrix M can be expressed as:

M=H ^(H)(HH ^(H)+φ_(nn))⁻¹.  Eq(11)

[0100] Based on equations (10) and (11), the initial MMSE estimate{circumflex over (x)} of the transmitted symbol vector x can bedetermined as: $\begin{matrix}\begin{matrix}{\underset{\_}{\hat{x}} = \quad {M\underset{\_}{r}}} \\{= \quad {{H^{H}\left( {{HH}^{H} + \varphi_{nn}} \right)}^{- 1}{\underset{\_}{r}.}}}\end{matrix} & {{Eq}\quad (12)}\end{matrix}$

[0101] To determine the SNR of the transmission channels for the UMMSEtechnique, the signal component can first be determined based on themean of {circumflex over (x)} given x, averaged over the additive noise,which can be expressed as: $\begin{matrix}{{E\left\lbrack \underset{\_}{\hat{x}} \middle| \underset{\_}{x} \right\rbrack} = {E\left\lbrack {M\quad \underset{\_}{r}} \middle| \underset{\_}{x} \right\rbrack}} \\{= {{H^{H}\left( {{H\quad H^{H}} + \varphi_{n\quad n}} \right)}^{- 1}{E\left\lbrack \underset{\_}{r} \right\rbrack}}} \\{= {{H^{H}\left( {{H\quad H^{H}} + \varphi_{n\quad n}} \right)}^{- 1}H\quad \underset{\_}{x}}} \\{{= {V\underset{\_}{\quad x}}},}\end{matrix}\quad$

[0102] where the matrix V is defined as: $\begin{matrix}{V = \left\{ v_{ij} \right\}} \\{= {M\quad H}} \\{= {{H^{H}\left( {{HH}^{H} + \varphi_{nn}} \right)}^{- 1}{H.}}}\end{matrix}\quad$

[0103] Using the identity

(HH ^(H)+φ_(nn))⁻¹=φ_(nn) ⁻¹−φ_(nn) ⁻¹ H(I+H ^(H)φ_(nn) ⁻¹ H)⁻¹ H^(H)φ_(nn) ⁻¹,

[0104] the matrix V can be expressed as:

V=H ^(H)φ_(nn) ³¹ ¹ H(I+H ^(H)φ_(nn) ⁻¹ H)⁻¹.

[0105] The i-th element of the initial MMSE estimate {circumflex over(x)}, {circumflex over (x)}_(i), can be expressed as:

{circumflex over (x)} _(i) =v _(i1) x ₁ + . . . +v _(ii) x _(i) + . . .+v _(iN) _(R) x _(N) _(R) .  Eq(13)

[0106] If all of the elements of {circumflex over (x)} are uncorrelatedand have zero mean, the expected value of the i-th element of{circumflex over (x)} can be expressed as:

E[{circumflex over (x)} _(i) |x]=v _(ii) x _(i).  Eq(14)

[0107] As shown in equation (14), {circumflex over (x)}_(i) is a biasedestimate of x_(i). This bias can be removed to obtain improved receiverperformance in accordance with the UMMSE technique. An unbiased estimateof x_(i) can be obtained by dividing {circumflex over (x)}_(i) byv_(ii). Thus, the unbiased minimum mean square error estimate of x,{tilde over (x)}, can be obtained by pre-multiplying the biased estimate{circumflex over (x)} by a diagonal matrix D_(v) ⁻¹, as follows:

{tilde over (x)}=D _(v) ⁻¹ {circumflex over (x)},  Eq(15)

[0108] where

D _(v) ⁻¹=diag(1/v ₁₁, 1/v ₂₂, . . . ,1/v _(N) _(R) _(N) _(R) ).

[0109] To determine the noise plus interference, the error ê between theunbiased estimate {tilde over (x)} and the transmitted symbol vector xcan be expressed as: $\quad \begin{matrix}{\underset{\_}{\hat{e}} = \quad {\underset{\_}{x} - {D_{v}^{- 1}\underset{\_}{\hat{x}}}}} \\{= \quad {\underset{\_}{x} - {D_{v}^{- 1}{H^{H}\left( {{HH}^{H} + \varphi_{nn}} \right)}^{- 1}{\underset{\_}{r}.}}}}\end{matrix}$

[0110] The autocorrelation matrix of the error vector ê can be expressedas: $\begin{matrix}{{\varphi_{\hat{e}\hat{e}} \cong \quad U \cong \left\{ u_{ij} \right\}} = {E\left\lbrack {\hat{e}{\hat{e}}^{H}} \right\rbrack}} \\{= \quad {I - {D_{V}^{- 1}{H^{H}\left( {{HH}^{H} + \varphi_{nn}} \right)}^{- 1}{H\left( {1 - {\frac{1}{2}D_{V}^{- 1}}} \right)}} -}} \\{\quad {\left( {1 - {\frac{1}{2}D_{V}^{- 1}}} \right){H^{H}\left( {{HH}^{H} + \varphi_{nn}} \right)}^{- 1}{{HD}_{V}^{- 1}.}}}\end{matrix}$

[0111] The variance of the i-th element of the error vector ê is equalto u_(ii). The elements of the error vector ê are correlated. However,sufficient interleaving may be used such that the correlation betweenthe elements of the error vector ê can be ignored and only the varianceaffects system performance.

[0112] If the components of the channel noise are uncorrelated and iid,the correlation matrix of the channel noise can be expressed as shown inequation (5). In that case, the autocorrelation matrix of the errorvector ê can be expressed as: $\begin{matrix}{\begin{matrix}{\varphi_{\hat{e}\quad \hat{e}} = \quad {I - {{D_{x}^{- 1}\left\lbrack {I - {\sigma_{n}^{2}\left( {{\sigma_{n}^{2}I} + R} \right)}^{- 1}} \right\rbrack}\left( {I - {\frac{1}{2}D_{x}^{- 1}}} \right)} -}} \\{\quad {{\left( {I - {\frac{1}{2}D_{x}^{- 1}}} \right)\left\lbrack {I - {\sigma_{n}^{2}\left( {{\sigma_{n}^{2}I} + R} \right)}^{- 1}} \right\rbrack}D_{x}^{- 1}}} \\{= \quad {U = {\left\{ u_{ij} \right\}.}}}\end{matrix}\quad} & {{Eq}\quad (16)}\end{matrix}$

[0113] And if the components of the channel noise are uncorrelated, then$\begin{matrix}{U = {I - {D_{V}^{- 1}{H^{H}\left( {{HH}^{H} + \varphi_{nn}} \right)}^{- 1}{H\left( {I - {\frac{1}{2}D_{V}^{- 1}}} \right)}} - {\left( {I - {\frac{1}{2}D_{V}^{- 1}}} \right){H^{H}\left( {{HH}^{H} + \varphi_{nn}} \right)}^{- 1}{{HD}_{V}^{- 1}.}}}} & {{Eq}\quad (17)}\end{matrix}$

[0114] The SNR of the demodulator output corresponding to the i-thtransmitted symbol can be expressed as: $\begin{matrix}{{SNR}_{i} = {\frac{E\left\lbrack \overset{\_}{{x_{i}}^{2}} \right\rbrack}{u_{ii}}.}} & {{Eq}\quad (18)}\end{matrix}$

[0115] If the variance, {overscore (|x_(i)|²)}, of the processedreceived symbols, x_(i), is equal to one (1.0) on the average, the SNRof for the receive symbol vector may be expressed as:${SNR}_{i} = {\frac{1}{u_{ii}}.}$

[0116]FIG. 6 shows an embodiment of an RX MIMO processor 156 b, which iscapable of implementing the UMMSE processing described above. Similar tothe CCMI method, the matrices H and φ_(nn) may be first estimated basedon the received pilot signals and/or data transmissions. The weightingcoefficient matrix M is then computed according to equation (11). WithinRX MIMO processor 156 b, the modulation symbols from the N_(R) receiveantennas are multiplexed by a multiplexer 612 to form a stream ofreceived modulation symbol vectors r. The received modulation symbolvectors r are then pre-multiplied by a multiplier 614 with the matrix Mto form an estimate {circumflex over (x)} of the transmitted symbolvector x, as shown above in equation (10). The estimate {circumflex over(x)} is further pre-multiplied by a multiplier 618 with the diagonalmatrix D_(v) ⁻¹ to form an unbiased estimate {tilde over (x)} of thetransmitted symbol vector x, as shown above in equation (15).

[0117] Again, depending on the particular communication mode beingimplemented, the subchannel symbol streams from all antennas used forthe transmission of the channel data stream may be provided to acombiner 618, which combines redundant information across time, space,and frequency. The combined modulation symbols {tilde over (x)}″ arethen provided to RX data processor 158. And for some other communicationmodes, the estimated modulation symbols {tilde over (x)} may be provideddirectly to RX data processor 158.

[0118] The unbiased estimated modulation symbols {tilde over (x)} and/orthe combined modulation symbols {tilde over (x)}″ are also provided to aCSI processor 620, which determines full or partial CSI for thetransmission channels and provides the full/partial-CSI to be reportedback to transmitter system 110. For example, CSI processor 620 mayestimate the SNR of the i-th transmission channel according to equations(16) through (18). The SNR for the transmission channels comprises thepartial-CSI that is reported back to the transmitter system. The optimalM as computed in equation (11) should already minimize the norm of theerror vector. D_(v) is computed in accordance with equation (16).

MIMO Receiver Utilizing Full-CSI Technique

[0119] For the full-CSI technique, the received signals at the output ofthe N_(R) receive antennas may be expressed as shown above in equation(2), which is:

r=Hx+n.

[0120] The eigenvector decomposition of the Hermitian matrix formed bythe product of the channel matrix with its conjugate-transpose can beexpressed as:

H ^(H) H=EΛ.E ^(H),

[0121] where E is the eigenvector matrix, and Λ is a diagonal matrix ofeigenvalues, both of dimension N_(T)×N_(T). The transmitterpreconditions a set of N_(T) modulation symbols b using the eigenvectormatrix E, as shown above in equation (1). The transmitted(preconditioned) modulation symbols from the N_(T) transmit antennas canthus be expressed as:

x=Eb.

[0122] Since H^(H)H is Hermitian, the eigenvector matrix is unitary.Thus, if the elements of b have equal power, the elements of x also haveequal power. The received signal may then be expressed as:

r=HEb+n.  Eq(19)

[0123] The receiver performs a channel-matched-filter operation,followed by multiplication by the right eigenvectors. The result of thechannel-matched-filter and multiplication operations is a vector z,which can be expressed as:

z=E ^(H) H ^(H) HEb+E ^(H) H ^(H) n=Λb+n′,  Eq(20)

[0124] where the new noise term has covariance that can be expressed as:

E({circumflex over (n)}{circumflex over (n)} ^(H))=E(E ^(H) H ^(H) nn^(H) HE)=E ^(H) H ^(H) HE=Λ,  Eq(21)

[0125] i.e., the noise components are independent with variance given bythe eigenvalues. The SNR of the i-th component of z is λ_(i), the i-thdiagonal element of Λ.

[0126] Full-CSI processing is described in further detail in theaforementioned U.S patent application Ser. No. 09/532,492.

[0127] The receiver embodiment shown in FIG. 5 may also be used toimplement the full-CSI technique. The received modulation symbol vectorsr are filtered by match filter 514, which pre-multiplies each vector rwith the conjugate-transpose channel coefficient matrix H^(H), as shownabove in equation (20). The filtered vectors are further pre-multipliedby multiplier 516 with the right eigenvectors E^(H) to form an estimatez of the modulation symbol vector b as shown above in equation (20). Forthe full-CSI technique, matrix processor 524 is configured to providethe right eigenvectors E^(H). The subsequent processing (e.g., bycombiner 518 and RX data processor 158) may be achieved as describedabove.

[0128] For the full-CSI technique, the transmitter unit can select acoding scheme and a modulation scheme (i.e., a signal constellation) foreach of the eigenvectors based on the SNR that is given by theeigenvalue. Providing that the channel conditions do not changeappreciably in the interval between the time the CSI is measured at thereceiver and reported and used to precondition the transmission at thetransmitter, the performance of the communications system may beequivalent to that of a set of independent AWGN channels with knownSNRs.

Reporting Full or Partial CSI Back to the Transmitter System

[0129] Using either the partial-CSI (e.g., CCMI or UMMSE) or full-CSItechnique described herein, the SNR of each transmission channel may beobtained for the received signals. The determined SNR for thetransmission channels may then be reported back to the transmittersystem via a reverse channel. By feeding back the SNR values of thetransmitted modulation symbols for the transmission channels (i.e., foreach spatial subchannel, and possibly for each frequency subchannel ifOFDM is employed), it is possible to implement adaptive processing(e.g., adaptive coding and modulation) to improve utilization of theMIMO channel. For the partial-CSI feedback techniques, adaptiveprocessing may be achieved without complete CSI. For the full-CSIfeedback techniques, sufficient information (and not necessarily theexplicit eigenvalues and eignemodes) is fed back to the transmitter tofacilitate calculation of the eigenvalues and eigenmodes for eachfrequency subchannel utilized.

[0130] For the CCMI technique, the SNR values of the received modulationsymbols (e.g., SNR_(i)={overscore (|x′_(i)|²)}/σ_(n′) ² orSNR_(i)=1/σ_(n) ²{haeck over (r)}_(ii) for the symbol received on thei-th transmission channel) are fed back to the transmitter. For theUMMSE technique, the SNR values of the received modulation symbols(e.g., SNR_(i)=E[|x_(i)|²]/u_(ii) or SNR_(i)=1/u_(ii) for the symbolreceived on the i-th transmission channel, with u_(ii) being computed asshown above in equations (16) and (17)) are fed back to the transmitter.And for the full-CSI technique, the SNR values of the receivedmodulation symbols (e.g., SNR_(i)={overscore (|z_(i)|²)}/σ_(n′) ² orSNR_(i)=λ_(ii)/σ_(n) ² for the symbol received on the i-th transmissionchannel, where λ_(ii) is the eigenvalue of the square matrix R) can befed back to the transmitter. For the full-CSI technique, the eigenmodesE may be further determined and fed back to the transmitter. For thepartial and full-CSI techniques, the SNR are used at the transmittersystem to adjust the processing of the data. And for the fill-CSItechnique, the eigenmodes E are further used to precondition themodulation symbols prior to transmission.

[0131] The CSI to be reported back to the transmitter may be sent infull, differentially, or a combination thereof. In one embodiment, fullor partial CSI is reported periodically, and differential updates aresent based on the prior transmitted CSI. As an example for full CSI, theupdates may be corrections (based on an error signal) to the reportedeigenmodes. The eigenvalues typically do not change as rapidly as theeigenmodes, so these may be updated at a lower rate. In anotherembodiment, the CSI is sent only when there is a change (e.g., if thechange exceeds a particular threshold), which may lower the effectiverate of the feedback channel. As an example for partial CSI, the SNRsmay be sent back (e.g., differentially) only when they change. For anOFDM system (with or without MIMO), correlation in the frequency domainmay be exploited to permit reduction in the amount of CSI to be fedback. As an example for an OFDM system using partial CSI, if the SNRcorresponding to a particular spatial subchannel for M frequencysubchannels is the same, the SNR and the first and last frequencysubchannels for which this condition is true may be reported. Othercompression and feedback channel error recovery techniques to reduce theamount of data to be fed back for CSI may also be used and are withinthe scope of the invention.

[0132] Referring back to FIG. 1, the full or partial-CSI (e.g., channelSNR) determined by RX MIMO processor 156 is provided to a TX dataprocessor 162, which processes the CSI and provides processed data toone or more modulators 154. Modulators 154 further condition theprocessed data and transmit the CSI back to transmitter system 110 via areverse channel.

[0133] At system 110, the transmitted feedback signal is received byantennas 124, demodulated by demodulators 122, and provided to a RX dataprocessor 132. RX data processor 132 performs processing complementaryto that performed by TX data processor 162 and recovers the reportedfull/partial-CSI, which is then provided to, and used to adjust theprocessing by, TX data processor 114 and TX MIMO processor 120.

[0134] Transmitter system 110 may adjust (i.e., adapt) its processingbased on the full/partial-CSI (e.g., SNR information) from receiversystem 150. For example, the coding for each transmission channel may beadjusted such that the information bit rate matches the transmissioncapability supported by the channel SNR. Additionally, the modulationscheme for the transmission channel may be selected based on the channelSNR. Other processing (e.g., interleaving) may also be adjusted and arewithin the scope of the invention. The adjustment of the processing foreach transmission channel based on the determined SNR for the channelallows the MIMO system to achieve high performance (i.e., highthroughput or bit rate for a particular level of performance). Theadaptive processing can be applied to a single-carrier MIMO system or amulti-carrier based MIMO system (e.g., a MIMO system utilizing OFDM).

[0135] The adjustment in the coding and the selection of the modulationscheme at the transmitter system may be achieved based on numeroustechniques, one of which is described in the aforementioned U.S. patentapplication Ser. No. 09/776,073.

[0136] The partial (e.g., CCMI and UMMSE) and full-CSI techniques arereceiver processing techniques that allow a MIMO system to utilize theadditional dimensionalities created by the use of multiple transmit andreceive antennas, which is a main advantage for employing MIMO. The CCMIand UMMSE techniques may allow the same number of modulation symbols tobe transmitted for each time slot as for a MIMO system utilizing fullCSI. However, other receiver processing techniques may also be used inconjunction with the full/partial-CSI feedback techniques describedherein and are within the scope of the invention. Analogously, FIGS. 5and 6 represent two embodiments of a receiver system capable ofprocessing a MIMO transmission, determining the characteristics of thetransmission channels (i.e., the SNR), and reporting full or partial CSIback to the transmitter system. Other designs based on the techniquespresented herein and other receiver processing techniques can becontemplated and are within the scope of the invention.

[0137] The partial-CSI technique (e.g., CCMI and UMMSE techniques) mayalso be used in a straightforward manner without adaptive processing atthe transmitter when only the overall received signal SNR or theattainable overall throughput estimated based on such SNR is feed back.In one implementation, a modulation format is determined based on thereceived SNR estimate or the estimated throughput, and the samemodulation format is used for all transmission channels. This method mayreduce the overall system throughput but may also greatly reduce theamount of information sent back over the reverse link.

[0138] Improvement in system performance may be realized with the use ofthe full/partial-CSI feedback techniques of the invention. The systemthroughput with partial CSI feedback can be computed and comparedagainst the throughput with full CSI feedback. The system throughput canbe defined as:${C = {\sum\limits_{i = 1}^{N_{c}}\quad {\log_{2}\left( {1 + \gamma_{i}} \right)}}},$

[0139] where γ₁ is the SNR of each received modulation symbol forpartial CSI techniques or the SNR of each transmission channel for thefull CSI technique. The SNR for various processing techniques can besummarized as follows: $\begin{matrix}{{\gamma_{i} = \quad \frac{1}{\sigma_{n}^{2}{\overset{\Cup}{r}}_{ii}}},} & {\quad {{for}\quad {the}\quad {CCMI}\quad {technique}}} \\{{\gamma_{i} = \quad \frac{1}{u_{ii}}},} & {\quad {{{for}\quad {the}\quad {UMMSE}\quad {technique}},{and}}} \\{{\gamma_{i} = \quad \frac{\lambda_{ii}}{\sigma_{n}^{2}}},} & {\quad {{for}\quad {full}\quad {CSI}\quad {{technique}.}}}\end{matrix}$

[0140]FIGS. 7A and 7B show the performance of a 4×4 MIMO systememploying partial-CSI and full-CSI feedback techniques. The results areobtained from a computer simulation. In the simulation, the elements ofeach channel coefficient matrix H are modeled as independent Gaussianrandom variable with zero mean and unity variance. For each calculation,a number of random matrix realizations are generated and the throughputcomputed for the realization are averaged to generate the averagethroughput.

[0141]FIG. 7A shows the average throughput for the MIMO system for thefull-CSI, partial-CSI CCMI, and partial-CSI UMMSE techniques fordifferent SNR values. It can be seen from FIG. 7A that the throughput ofthe partial-CSI UMMSE technique is approximately 75% of the full-SIthroughput at high SNR values, and approaches the full CSI throughput atlow SNR values. The throughput of the partial-CSI CCMI technique isapproximately 75%-90% of the throughput of the partial-CSI UMMSEtechnique at high SNR values, and is approximately less than 30% of theUMMSE throughput at low SNR values.

[0142]FIG. 7B shows the cumulative probability distribution functions(CDF) for the three techniques generated based on the histogram of thedata. FIG. 7B shows that at an average SNR of 16 dB per transmissionchannel, there are approximately 5% cases when the throughput is lessthan 2 bps/Hz for the CCMI technique. On the other hand, the throughputof the UMMSE technique is above 7.5 bps/Hz for all cases at the sameSNR. Thus, the UMMSE technique is likely to have lower outageprobability than the CCMI technique.

[0143] The elements of the transmitter and receiver systems may beimplemented with one or more digital signal processors (DSP),application specific integrated circuits (ASIC), processors,microprocessors, controllers, microcontrollers, field programmable gatearrays (FPGA), programmable logic devices, other electronic units, orany combination thereof. Some of the functions and processing describedherein may also be implemented with software executed on a processor.

[0144] Aspects of the invention may be implemented with a combination ofsoftware and hardware. For example, computations for the symbolestimates for the CCMI and UMMSE techniques and the derivation of thechannel SNR may be performed based on program codes executed on aprocessor (controllers 530 and 650 in FIGS. 5 and 6, respectively).

[0145] The previous description of the disclosed embodiments is providedto enable any person skilled in the art to make or use the presentinvention. Various modifications to these embodiments will be readilyapparent to those skilled in the art, and the generic principles definedherein may be applied to other embodiments without departing from thespirit or scope of the invention. Thus, the present invention is notintended to be limited to the embodiments shown herein but is to beaccorded the widest scope consistent with the principles and novelfeatures disclosed herein.

What is claimed is:
 1. A method for transmitting data from a transmitter unit to a receiver unit in a multiple-input multiple-output (MIMO) communication system, comprising: at the receiver unit, receiving a plurality of signals via a plurality of receive antennas, wherein the received signal from each receive antenna comprises a combination of one or more signals transmitted from the transmitter unit, processing the received signals to derive channel state information (CSI) indicative of characteristics of a plurality of transmission channels used for data transmission, and transmitting the CSI back to the transmitter unit; and at the transmitter unit, receiving the CSI from the receiver unit, and processing data for transmission to the receiver unit based on the received CSI.
 2. The method of claim 1, wherein the reported CSI comprises signal-to-noise-plus-interference (SNR) estimates for each of the plurality of transmission channels.
 3. The method of claim 2, wherein the processing at the transmitter unit includes coding data for each transmission channel based on the SNR estimate for the transmission channel.
 4. The method of claim 3, wherein the data for each transmission channel is independently coded based on the SNR estimate for the transmission channel.
 5. The method of claim 3, wherein the coding includes coding the data for the transmission channel with a fixed base code, and adjusting puncturing of coded bits based on the SNR estimate for the transmission channel.
 6. The method of claim 3, wherein the processing at the transmitter unit further includes modulating coded data for each transmission channel in accordance with a modulation scheme selected based on the SNR estimate for the transmission channel.
 7. The method of claim 1, wherein the reported CSI comprises characterizations for the plurality of transmission channels.
 8. The method of claim 1, wherein the reported CSI is indicative of eigenmodes and eigenvalues for the plurality of transmission channels.
 9. The method of claim 8, wherein the processing at the transmitter unit includes coding data for the transmission channels based on the eigenvalues.
 10. The method of claim 9, wherein the data for each transmission channel is independently coded.
 11. The method of claim 9, wherein the processing at the transmitter unit further includes modulating coded data for the transmission channels in accordance with modulation schemes selected based on the eigenvalues to provide modulation symbols.
 12. The method of claim 11, wherein the processing at the transmitter unit further includes pre-conditioning the modulation symbols prior to transmission based on the eigenmodes.
 13. The method of claim 1, wherein the CSI is transmitted in full from the receiver unit.
 14. The method of claim 13, wherein the CSI is periodically transmitted in full from the receiver unit, and wherein updates to the CSI are transmitted between full transmissions.
 15. The method of claim 1, wherein the CSI is transmitted when changes in the channel characteristics exceeding a particular threshold are detected.
 16. The method of claim 8, wherein the CSI indicative of the eigenmodes and eigenvalues are transmitted at different update rates.
 17. The method of claim 1, wherein the CSI is derived at the receiver unit based on a correlation matrix inversion (CCMI) processing.
 18. The method of claim 17, wherein the CCMI processing at the receiver unit includes processing the received signals to derive received modulation symbols; filtering the received modulation symbols in accordance with a first matrix to provide filtered modulation symbols, wherein the first matrix is representative of an estimate of channel characteristics between a plurality of transmit antennas and the plurality of receive antennas used for the data transmission; multiplying the filtered modulation symbols with a second matrix to provide estimates of transmitted modulation symbols; and estimating characteristics of a plurality of transmission channels used for the data transmission.
 19. The method of claim 18, further comprising: demodulating the modulation symbol estimates in accordance with a particular demodulation scheme to provide demodulated symbols.
 20. The method of claim 19, further comprising: decoding the demodulated symbols in accordance with a particular decoding scheme.
 21. The method of claim 18, further comprising: combining modulation symbol estimates for redundant transmission to provide combined modulation symbol estimates.
 22. The method of claim 18, further comprising: deriving a channel coefficient matrix based on the received modulation symbols, and wherein the first matrix is derived from the channel coefficient matrix.
 23. The method of claim 22, wherein the channel coefficient matrix is derived based on received modulation symbols corresponding to pilot data.
 24. The method of claim 18, wherein the second matrix is an inverse square matrix derived based on the first matrix.
 25. The method of claim 1, wherein the CSI is derived at the receiver unit based on an unbiased minimum mean square error (UMMSE) processing.
 26. The method of claim 25, wherein the UMMSE processing includes processing the received signals to derive received modulation symbols; multiplying the received modulation symbols with a first matrix M to provide estimates of transmitted modulation symbols; and estimating characteristics of a plurality of transmission channels used for the data transmission based on the received modulation symbol, and wherein the first matrix M is selected to minimize a mean square error between the modulation symbol estimates and transmitted modulation symbols.
 27. The method of claim 26, further comprising: multiplying the modulation symbol estimates with a second matrix to provide unbiased estimates of the transmitted modulation symbols, and wherein the characteristics of the transmission channels are estimated based on the unbiased modulation symbol estimates.
 28. The method of claim 27, further comprising: deriving the first matrix M based on based on the unbiased modulation symbol estimates and to minimize the mean square error between the unbiased modulation symbol estimates and the transmitted modulation symbols.
 29. The method of claim 1, wherein the MIMO system implements orthogonal frequency division modulation (OFDM).
 30. The method of claim 29, wherein the processing at each of the receiver unit and transmitter unit is performed for each of a plurality of frequency subchannels.
 31. A method for transmitting data from a transmitter unit to a receiver unit in a multiple-input multiple-output (MIMO) communication system, comprising: at the receiver unit, receiving a plurality of signals via a plurality of receive antennas, wherein the received signal from each receive antenna comprises a combination of one or more signals transmitted from the transmitter unit, processing the plurality of received signals to provide estimates of modulation symbols transmitted from the transmitter unit, estimating signal-to-noise-plus-interference (SNR) of a plurality of transmission channels used for data transmission, and transmitting SNR estimates for the transmission channels back to the transmitter unit; and at the transmitter unit, processing data for transmission to the receiver unit in accordance with the received SNR estimates.
 32. The method of claim 31, wherein the SNR of each of the plurality of transmission channels is estimated, and the SNR estimates for each transmission channel is transmitted back to the transmitter unit.
 33. The method of claim 31, further comprising: at the receiver unit, deriving characterizations for the plurality of transmission channels used for data transmission, and transmitting the characterizations back to the transmitter unit.
 34. The method of claim 33, further comprising: at the transmitter unit, pre-conditioning modulation symbols prior to transmission to the receiver unit in accordance with characterizations for the plurality of transmission channels.
 35. The method of claim 31, wherein the received modulation symbols are processed in accordance with a channel correlation matrix inversion (CCMI) scheme.
 36. The method of claim 31, wherein the received modulation symbols are processed in accordance with a minimum unbiased mean square error (UMMSE) scheme.
 37. The method of claim 31, wherein the processing at the transmitter unit includes coding data for each transmission channel in accordance with the received SNR estimate for the transmission channel.
 38. The method of claim 37, wherein the processing of the processing at the transmitter unit further includes modulating coded data for each transmission channel based on a modulation scheme selected based on the received SNR estimate for the transmission channel.
 39. A multiple-input multiple-output (MIMO) communication system, comprising: a receiver unit comprising a plurality of front-end processors configured to receive a plurality of signals via a plurality of receive antennas and to process the received signals to provide received modulation symbols, at least one receive MIMO processor coupled to the front-end processors and configured to receive and process the received modulation symbols to derive channel state information (CSI) indicative of characteristics of a plurality of transmission channels used for data transmission, and a transmit data processor operatively coupled to the receive MIMO processor and configured to process the CSI for transmission back to the transmitter unit; and a transmitter unit comprising at least one demodulator configured to receive and process one or more signals from the receiver unit to recover the transmitted CSI, and a transmit data processor configured to process data for transmission to the receiver unit based on the recovered CSI.
 40. A receiver unit in a multiple-input multiple-output (MIMO) communication system, comprising: a plurality of front-end processors configured to receive a plurality of transmitted signals via a plurality of receive antennas and to process the received signals to provide received modulation symbols; a filter operatively coupled to the plurality of front-end processors and configured to filter the received modulation symbols in accordance with a first matrix to provide filtered modulation symbols, wherein the first matrix is representative of an estimate of channel characteristics between a plurality of transmit antennas and the plurality of receive antennas used for the data transmission; a multiplier coupled to the filter and configured to multiply the filtered modulation symbols with a second matrix to provide estimates of transmitted modulation symbols; a channel quality estimator coupled to the multiplier and configured to estimate characteristics of a plurality of transmission channels used for the data transmission and provide channel state information (CSI) indicative of the estimated channel characteristics; and a transmit data processor configured to receive and process the CSI for transmission from the receiver unit.
 41. The receiver unit of claim 40, further comprising: a second estimator configured to derive a channel coefficient matrix based on the modulation symbol estimates, and wherein the first matrix is derived based on the channel coefficient matrix.
 42. The receiver unit of claim 40, wherein the estimates of the transmission channel characteristics comprise signal-to-noise-plus-interference (SNR) estimates.
 43. The receiver unit of claim 40, further comprising: one or more demodulation elements, each demodulation element configured to receive and demodulate a respective stream of modulation symbol estimates in accordance with a particular demodulation scheme to provide a stream of demodulated symbols.
 44. The receiver unit of claim 43, further comprising: one or more decoders, each decoder configured to receive and decode a stream of demodulated symbols in accordance with a particular decoding scheme to provide decoded data. 